Introduction & Background

Rachel Venturino, UCLA; Michael Schall, UCLA; Jonathan Solichin, UCLA

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Increasing availability of publicly accessible remotely sensed data and software via Google Earth has provided a unique tool for the general public, allowing them to discern alterations of the global environment etc. which has historically been limited to industry professionals. Liberalization of this material permits the general public to analyze various global phenomenon that have proven difficult to convey abstractly. Provided pressing issues, ranging from climate change to real time storm tracking, these data sets can be utilized in new ways, from preventive studies to post-analysis. While there has been much movement in ways to acquire data, platforms for processing these data into information has been lacking. Presently, the only publicly available software known to the general public for remote sensing analysis is, by and large, Google Earth.

Despite initial, monumental changes in user access described above we presume that Google is neglecting to achieve the entirety of impact they could, based on deficiencies in further data manipulation. Applications such as ENVI allow users greater manipulation of imagery, yielding exponential benefit to analysis and processes not obtainable with the present functionality of Google Earth.


Presently, Google is making headway with their Google Earth Engine Beta project (hereafter: EE), a software currently available by sign up that allows remote sensing via their hosted cloud computation platform. Similarly, they have begun collecting data that is becoming more publicly available to augment their current remote sensing library, employed on Google Earth, through EE’s Data Catalog. They have similarly started projects in the academic space that demonstrates their interest in developing public awareness of remote sensing, for example: Global Forest Change in conjunction with the University of Maryland.

The present site will attempt to survey Google Earth Engine’s current capability, and how we can augment it with remote sensing data and processes used in academia. We hypothesize that some ENVI functions (i.e. spectral band selection, NDVI analysis, etc.), as well as basic algorithms often used in remote sensing, as well as data freely available for the public through USGS, NOAA, and so forth, can be baked into their publicly visible Google Earth Enging software through an intuitive GUI, Thus allowing Google to capitalize on some of the proprietary market share while empowering the public in unprecedented ways by increasing the visibility and viability of remote sensing.

Google is a quintessential player in the information age and if they seek to fulfill their aim “to organize the world’s information and make it universally accessible and useful” the aforementioned concepts are imperative in their business model [1].

Survey of Google Earth Engine for academia and in comparison with existing platforms and publicly available data.